Impact of COVID-19 epidemic curtailment strategies in selected Indian states: An analysis by reproduction number and doubling time with incidence modelling
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SciScore for 10.1101/2020.05.10.20094946: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The time bought should be utilized to intensify the surveillance among ‘at-risk’ individuals and buttress the health infrastructure including hospital beds with oxygen availability and critical care beds with ventilators and telemedicine.(24-26) The results of this study should be interpreted with certain caveats apart from the inherent limitations of crowd-sourcing nature of the data. The estimates might be influenced by certain effect …
SciScore for 10.1101/2020.05.10.20094946: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The time bought should be utilized to intensify the surveillance among ‘at-risk’ individuals and buttress the health infrastructure including hospital beds with oxygen availability and critical care beds with ventilators and telemedicine.(24-26) The results of this study should be interpreted with certain caveats apart from the inherent limitations of crowd-sourcing nature of the data. The estimates might be influenced by certain effect modifiers and confounders like population density, climatic variations and violation of assumption of random mixing, yet the methods are robust in terms of conditional independence and MCMC methods used to tackle the Bayesian influence. Conceptually, this phenomenon is dynamic and non-linear in nature and hence should be read with caution
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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SciScore for 10.1101/2020.05.10.20094946: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
The time bought should be utilized to intensify the surveillance among ‘at-risk’ individuals and buttress the health infrastructure including hospital beds with oxygen availability and critical care beds with ventilators and telemedicine.(24–26) The results of this study should be interpreted with certain caveats apart from the inherent limitations of crowd-sourcing nature of the data. The estimates might be influenced by certain …
SciScore for 10.1101/2020.05.10.20094946: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
The time bought should be utilized to intensify the surveillance among ‘at-risk’ individuals and buttress the health infrastructure including hospital beds with oxygen availability and critical care beds with ventilators and telemedicine.(24–26) The results of this study should be interpreted with certain caveats apart from the inherent limitations of crowd-sourcing nature of the data. The estimates might be influenced by certain effect modifiers and confounders like population density, climatic variations and violation of assumption of random mixing, yet the methods are robust in terms of conditional independence and MCMC methods used to tackle the Bayesian influence. Conceptually, this phenomenon is dynamic and non-linear in nature and hence should be read with caution Acknowledgement- We would like to thank the team of COVID-19 India Tracker (www.covid19india.org) for their initiative in envisioning and developing the website. We are grateful to the members of the 'Covid19India.org Folding@Home Team' Telegram group for their invaluable and continued support without which this manuscript would not be possible. Conflict of Interest- Nil Funding- None Supplementary FilesSupplementary Appendix-1: R-code for analysis Supplementary Appendix-2: Incidence modelling and projections Supplementary Table-1: Number of imported and local cases Supplementary Table-2 : Number of projected cases and actual cases
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
About SciScore
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